Nonsingular Terminal Sliding Mode Control Research Articles

Nonsingular Terminal Sliding Mode Control for Vehicular Platoon Systems with Measurement Delays and Noise

Platooning of vehicular systems has been considered an effective solution for alleviating traffic congestion and reducing energy consumption. Because of limitations in onboard sensors, the measurement system inevitably suffers from measurement delays and noise, yet it receives insufficient attention. In this article, to deal with the measurement delays and noise while improving convergence performance, the platoon control problem of vehicular systems is studied under the nonsingular terminal sliding mode control (NTSMC) framework. A sliding mode observer (SMO) is proposed to estimate the states affected by measurement delays and noise. A distributed NTSMC scheme is developed for the platooning of the vehicular systems and ensures the convergence of the sliding mode surface affected by measurement delays and noise. One salient feature of the proposed SMO is that it can handle time-varying measurement delays rather than constant ones. Moreover, the control law is free of initial spacing error conditions under the employed coupled spacing policy. Numerical simulations are finally provided to demonstrate the effectiveness and efficiency of the proposed algorithm.

Lower limb exoskeleton for gait rehabilitation with adaptive nonsingular sliding mode control

Abstract This paper introduces a lower limb exoskeleton for gait rehabilitation, which has been designed to be adjustable to a wide range of patients by incorporating an extension mechanism and series elastic actuators (SEAs). This configuration adapts better to the user’s anatomy and the natural movements of the user’s joints. However, the inclusion of SEAs increases actuator mass and size, while also introducing nonlinearities and changes in the dynamic response of the exoskeletons. To address the challenges related to the human–exoskeleton dynamic interaction, a nonsingular terminal sliding mode control that integrates an adaptive parameter adjustment strategy is proposed, offering a practical solution for trajectory tracking with uncertain exoskeleton dynamics. Simulation results demonstrate the algorithm’s ability to estimate unknown parameters. Experimental tests analyze the performance of the controller against uncertainties and external disturbances.

Super-twisting nonsingular terminal sliding mode control for cyber physical system under FDI attacks

Super-twisting nonsingular terminal sliding mode control for cyber physical system under FDI attacks

Enhanced Impedance Control of Cable-Driven Unmanned Aerial Manipulators Using Fractional-Order Nonsingular Terminal Sliding Mode Control with Disturbance Observer Integration

The article presents a novel control strategy for cable-driven aerial manipulators (UAMs) aimed at enhancing impedance control during contact operations in complex environments. A fractional-order nonsingular terminal sliding mode control (FONTSMC) integrated with a disturbance observer (DOB) is proposed to improve the robustness and precision of the UAM under lumped disturbances. This developed approach utilizes the flexibility of fractional calculus, the finite-time stability of nonsingular terminal sliding mode, and the real-time disturbance estimation capabilities of the DOB to ensure smooth and compliant contact interactions. The effectiveness of the proposed control strategy is validated through comprehensive simulation studies, which demonstrate significant improvements in control performance, stability, and disturbance rejection when compared to traditional methods. The results indicate that the FONTSMC-DOB framework is highly suitable for complex aerial manipulation tasks, offering both theoretical and practical insights into the design of advanced control systems for UAMs.

Rapid attitude stabilization of ultra-low orbit satellites using movable masses and reaction wheels

This paper proposes a combination of movable masses and reaction wheels for the attitude control of ultra-low-orbit satellites. During the attitude control of ultra-low-orbit satellites, the satellite’s attitude is significantly influenced by the aerodynamic torque. Therefore, this paper proposes a combined control method using movable masses and reaction wheels. By adjusting the position of the movable masses to modify the relative distance between the center of mass (CM) and the center of pressure (CP), the aerodynamic torque is effectively reduced. Additionally, a finite-time terminal sliding mode extended state observer (TSMESO) is incorporated to estimate the reduced aerodynamic torque. Then, a finite-time non-singular terminal sliding mode control (NTSMC) method is introduced to achieve rapid attitude stabilization. Simulations demonstrate that under the proposed control system, the aerodynamic torque acting on the ultra-low-orbit spacecraft can be significantly reduced in a short time, and the response and high precision attitude stability can be effectively achieved.

A reinforcement learning based sliding mode control for passive upper-limb exoskeleton

Rehabilitation devices such as actuated exoskeletons can provide mobility assistance for patients suffering from paralysis or muscle weakness. In order to improve the well-being of patients, the control design of exoskeletons is of paramount importance and highest priority. In this paper, we present a sliding reinforcement learning (RL) method control for an upper-limb exoskeleton, enabling it to learn following a desired trajectory in the Cartesian space. The deep deterministic policy gradient (DDPG) using an actor-critic architecture is employed to continuously adjust the non-singular terminal sliding mode control (NSTSMC) control inputs, based on previous experiences. The designed actor network learns the policy and the critic evaluates the quality of the actions chosen by the actor. The robustness of the proposed approach is studied when the system is subjected to random disturbances. The simulation results demonstrate that the proposed approach based on the RL method effectively fulfills exoskeleton tracking tasks. Moreover, a comparative analysis with the standard NSTSMC, computed torque (CT), and RL-based CT shows the superiority of the proposed approach in terms of position tracking error. These findings are further confirmed by various performance evaluation metrics.

Hierarchical Nonsingular Terminal Sliding Mode Control With Finite-Time Disturbance Observer for PMSM Speed Regulation System

Hierarchical Nonsingular Terminal Sliding Mode Control With Finite-Time Disturbance Observer for PMSM Speed Regulation System

An Adaptive Characteristic Model-Based Event-Triggered Sigmoid Prescribed Performance Control Approach for Tracking the Trajectory of Autonomous Underwater Vehicles

This paper introduces an event-triggered sigmoid prescribed performance control method, enhanced by an adaptive characteristic model, for tracking the trajectory of autonomous underwater vehicles (AUVs). The AUV model is simplified into a function reliant solely on second-order parameter information through the use of characteristic modeling and a compression algorithm, which is then approximated by a neural network. We propose integrating prescribed performance control into event-triggered sliding mode control to accelerate convergence in AUV trajectory tracking. A novel prescribed performance function is employed in this integration, creating an event-triggered, non-singular terminal sliding mode control strategy. The stability of this controller is rigorously proven. This control strategy is not only robust against model uncertainties but also mitigates the jitter commonly associated with sliding mode control and the singularities from preset performance control due to sudden random disturbances. Comparative simulation experiments demonstrate that the proposed control method achieves superior control accuracy and a quicker response.

Fast non-singular terminal sliding mode control of the cubesat attitude for on-orbit assembly process

Fast non-singular terminal sliding mode control of the cubesat attitude for on-orbit assembly process

Adaptive disturbance observer-based fast nonsingular terminal sliding mode control for quadrotors

In this paper, a sliding-mode disturbance observer (SMDO)-based finite-time control scheme is proposed for a quadrotor under uncertainties and external disturbances. The SMDO is used to estimate and compensate the unknown time-varying disturbance with minor chattering and rapid convergence. However, a priori bounded uncertainty may impose a priori constraint on the system state before obtaining closed-loop stability. To address this issue, an adaptive SMDO (ASMDO) with a nested adaptive structure is further introduced. As for controller design, a fast nonsingular integral terminal sliding mode controller (FNITSMC) is proposed to ensure finite-time convergence and zero tracking error for the quadrotor attitude control. Finally, effectiveness of proposed method is verified through simulations and experiments.

Non-singular terminal sliding mode control algorithm design based on extended state observer

Non-singular terminal sliding mode control algorithm design based on extended state observer

Cooperative control of variable damping error port Hamiltonian and backstepping nonsingular terminal sliding mode control for manipulators driven by PMSMs

AbstractTo improve the disadvantages of signal control and energy control, a cooperative control strategy combining signal control and energy control is proposed for manipulators driven by permanent magnet synchronous motors (PMSMs) in this article. The cooperative control strategy is achieved by way of the convex combination of signal controller and energy controller, and Gaussian function is selected as cooperative function. The energy controller applies variable damping error port Hamiltonian and the signal controller uses backstepping nonsingular terminal sliding mode control. The PMSM with loss model is applied to obtain higher efficiency. To deal with modeling errors and joint friction, a nonlinear disturbance observer is used for manipulators system. Simulation and experiment results display that the designed strategy not only increases efficiency, but also enhances dynamic and steady‐state performance of manipulators.

Safe affine formation using terminal sliding mode control with input constraints

AbstractFormation control is a fundamental task in the realm of autonomous multiagent systems. To drive a group of agents to maneuver continuously with the desired formation, this paper studies the finite‐time affine formation control problem with disturbances, input constraints and safety guarantee. A non‐singular terminal sliding mode control (NTSMC) is implemented to achieve finite‐time convergence of all followers to their desired positions. Additionally, an auxiliary system is deployed to address input constraints resulting from the physical properties of the affine formation system. To mitigate the impact of lumped disturbances, a finite‐time disturbance observer (FTDO) is employed to estimate the disturbances and compensate for their effects. Based on FTDO, the auxiliary system and the above NTSMC, a finite‐time robust controller is developed as the nominal controller. By modifying the nominal controllers to comply with safety constraints, control barrier functions are employed to ensure the safety of the formation system in obstacle‐filled environment. Finally, the effectiveness and feasibility of this method are validated through simulations and real‐world experiments.

Multiple feedback recurrent neural network based super-twisting predefined-time nonsingular terminal sliding mode control for quad-rotor UAV

This research deals with the overall predefined-time stability (PTS) of Unmanned Aerial Vehicles (UAV) ensuring rapid convergence based on a novel sliding mode control (SMC). The strength of predefined-time sliding manifolds lies in the convergence rate can be adjusted by an explicit parameter. For the limitation of chattering encountered by predefined-time SMC (PTSMC), a variable gain super-twisting algorithm (STA) with additional linear items is designed as the switch controller. To conserve the restrained computational resources of quadrotors, the equivalent control input is approximated by a multiple feedback recurrent neural network (MFRNN) directly, which is challenging for general recurrent neural networks. The proposed MFRNN is characterized by the incorporation of double-loop feedback within the layers, augmenting its capacity for accurate approximation. To address the vanishing gradients commonly encountered with traditional activation functions, LeakyRelu is chosen. The Lyapunov theory is utilized to ensure the PTS of overall system and obtain the MFRNN weight update laws. An experiment is conducted to validate the proposed scheme.

Novel distributed event/self-triggered sliding-mode control: Application to practical fixed-time consensus of second-order multi-agent systems

This paper presents a novel terminal sliding-mode control (SMC) protocol to accomplish the practical fixed-time (PFXT) consensus of second-order multi-agent systems (MASs) through event-triggered scheme (ETS). The main challenge is the digitization of SMC which prevents the controlled system from reaching an ideal sliding phase and the singularity problem in terminal sliding-mode controllers. Firstly, a novel method of PFXT stability is proposed, which guarantees the non-singularity for the controller. Secondly, based on the proposed PFXT control method, a practical non-singular terminal SMC strategy is designed to accomplish the PFXT consensus of MASs through ETS. Besides, a strictly positive minimal triggering interval of each follower is given to exclude the Zeno phenomenon. Different with conventional terminal SMC, maintaining the sliding trajectory constrained on the sliding manifold is not a premise to guarantee the system stability. Then, to eliminate the requirement of continuous monitoring for ETS, the SMC strategy is generalized to the self-triggered approach. At last, a numerical example is presented to validate the developed methods.

Active Fault Tolerant Nonsingular Terminal Sliding Mode Control for Electromechanical System Based on Support Vector Machine

Effective fault diagnosis and fault-tolerant control method for aeronautics electromechanical actuator is concerned in this paper. By borrowing the advantages of model-driven and data-driven methods, a fault tolerant nonsingular terminal sliding mode control method based on support vector machine (SVM) is proposed. A SVM is designed to estimate the fault by off-line learning from small sample data with solving convex quadratic programming method and is introduced into a high-gain observer, so as to improve the state estimation and fault detection accuracy when the fault occurs. The state estimation value of the observer is used for state reconfiguration. A novel nonsingular terminal sliding mode surface is designed, and Lyapunov theorem is used to derive a parameter adaptation law and a control law. It is guaranteed that the proposed controller can achieve asymptotical stability which is superior to many advanced fault-tolerant controllers. In addition, the parameter estimation also can help to diagnose the system faults because the faults can be reflected by the parameters variation. Extensive comparative simulation and experimental results illustrate the effectiveness and advancement of the proposed controller compared with several other main-stream controllers.

Composite control based on FNTSMC and adaptive neural network for PMSM system

In this paper, a novel fixed-time non-singular terminal sliding mode control (NFNTSMC) method with an adaptive neural network (ANN) is proposed for permanent magnet synchronous motor (PMSM) system to improve PMSM performance. For nominal PMSM system without disturbance, a novel fixed-time non-singular terminal sliding mode control is designed to achieve fixed-time convergence property to improve the dynamic performance of the system. However, parameters mismatch and external load disturbances generally exist in PMSM system, the controller designed by NFNTSMC requires a large switching gain to ensure the robustness of the system, which will cause high-frequency sliding mode chattering. Therefore, an adaptive radial basis function (RBF) neural network is designed to approximate the unknown nonlinear lumped disturbance including parameters mismatch and external load disturbances online, and then the output of the neural network can be compensated to the NFNTSMC controller to reduce the switching gain and sliding mode chattering. Finally, the fixed-time convergence property and stability of the system are proved by Lyapunov method. The simulation and experimental results show that the presented strategy possesses satisfactory dynamic performance and strong robustness for PMSM system. And the proposed control scheme also provides an effective and systematic idea of the controller design for PMSM.

Adaptive fractional-order nonsingular terminal sliding mode control and sequential quadratic programming torque distribution for lateral stability of FWID-EVs with actuator constraints

This paper proposes a novel sliding mode control (SMC) algorithm for direct yaw moment control of four-wheel independent drive electric vehicles (FWID-EVs). The algorithm integrates adaptive law theory, fractional-order theory, and nonsingular terminal sliding mode reaching law theory to reduce chattering, handle uncertainty, and avoid singularities in the SMC system. A sequential quadratic programming (SQP) method is also proposed to optimize the yaw moment distribution under actuator constraints. The performance of the proposed algorithm is evaluated by a hardware-in-the-loop test with two driving maneuvers and compared with two existing SMC-based schemes together with the cases with the change of vehicle parameters and disturbances. The results demonstrate that the proposed algorithm can eliminate chattering and achieve the best lateral stability as compared with the existing schemes.

Adaptive backstepping sliding mode compensation control for electro‐hydraulic load simulator with backlash links

AbstractWhen a mechanical backlash between the loading piston rod and the steering gear piston rod connection of the electro‐hydraulic load simulator (EHLS), it will lead to poor loading accuracy. To solve this problem, an adaptive backstepping sliding mode controller based on the backlash feedforward compensation and state observer is proposed. First, the mechanism of surplus force generation in the EHLS is analyzed, and a mathematical model containing position disturbance and backlash nonlinearity is established based on the analysis results. Second, a state observer is designed to estimate the system state and the parameter adaptive law is designed to estimate the system parameters. Third, the adaptive backstepping method is combined with the non‐singular terminal sliding mode control (NTSMC) strategy to deal with the position disturbance and parameter uncertainty and to enhance the system's dynamic performance. Finally, a backlash feed‐forward compensator is engineered to restrain the detrimental effects caused by the backlash nonlinearity, and the simulation experimental results show that the designed new method can realize the precise loading of the EHLS under different working conditions, and the surplus force is suppressed better at the same time.

A novel adaptive fast sliding mode control method based on fuzzy algorithm for the air management system of fuel cell stack

Proton exchange membrane fuel cells (PEMFCs) offer advantages, such as, cleanliness, high efficiency, and environmental friendliness. To achieve optimal control of the PEMFC stack's air supply and management system under complex operating conditions, a novel non-singular terminal sliding mode controller based on fuzzy algorithm is proposed. Compared with the conventional sliding mode control, the terminal sliding mode control exhibits further performance improvements. However, it still has limitations. The proposed innovative sliding mode structure would ensure finite-time convergence and avoid the issue of singularity associated with terminal sliding mode control. Moreover, fuzzy logic makes sliding mode gain adapt to the system and further enhances the performance and stability, which is benefited from a stronger sliding surface. Results indicate that, compared with the other controllers, the designed controller could reduce delay further and provide faster response to sudden changes. The overshoot of sliding surface has decreased by 70% compared to its previous level. This novel control approach significantly enhances the efficiency and reliability of the PEMFC system.